Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

/pdf/image-quality-assessment-from-error-visibility-to-structural-1rlwcqe34t.pdf

Image quality assessment: from error visibility to structural similarity

There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

http://ahvazdownload.persiangig.com/document/article/39.pdf

A wavelet tour of signal processing

Embedded zerotree wavelet (EZW) coding, introduced by Shapiro (see IEEE Trans. Signal Processing, vol.41, no.12, p.3445, 1993), is a very effective and computationally simple technique for image compression. We offer an alternative explanation of the principles of its operation, so that the reasons for its excellent performance can be better understood. These principles are partial ordering by magnitude with a set partitioning sorting algorithm, ordered bit plane transmission, and exploitation of self-similarity across different scales of an image wavelet transform. Moreover, we present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than our previously reported extension of EZW that surpassed the performance of the original EZW. The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods. In addition, the new coding and decoding procedures are extremely fast, and they can be made even faster, with only small loss in performance, by omitting entropy coding of the bit stream by the arithmetic code.

http://dns2.asia.edu.tw/~ysho/YSHO-English/2000%20Engineering/PDF/IEE%20Tra%20Cir%20Sys%20Vid%20Tec6,%20243.pdf

A new, fast, and efficient image codec based on set partitioning in hierarchical trees

The embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkably effective, image compression algorithm, having the property that the bits in the bit stream are generated in order of importance, yielding a fully embedded code The embedded code represents a sequence of binary decisions that distinguish an image from the "null" image Using an embedded coding algorithm, an encoder can terminate the encoding at any point thereby allowing a target rate or target distortion metric to be met exactly Also, given a bit stream, the decoder can cease decoding at any point in the bit stream and still produce exactly the same image that would have been encoded at the bit rate corresponding to the truncated bit stream In addition to producing a fully embedded bit stream, the EZW consistently produces compression results that are competitive with virtually all known compression algorithms on standard test images Yet this performance is achieved with a technique that requires absolutely no training, no pre-stored tables or codebooks, and requires no prior knowledge of the image source The EZW algorithm is based on four key concepts: (1) a discrete wavelet transform or hierarchical subband decomposition, (2) prediction of the absence of significant information across scales by exploiting the self-similarity inherent in images, (3) entropy-coded successive-approximation quantization, and (4) universal lossless data compression which is achieved via adaptive arithmetic coding >

http://dns2.asia.edu.tw/~ysho/YSHO-English/2000%20Engineering/PDF/IEE%20Tra%20Sig%20Pro41,%203445.pdf

Embedded image coding using zerotrees of wavelet coefficients

The use of kernel Fisher discriminants is used to detect the presence of JPEG
based hiding methods. The feature vector for the kernel discriminant is constructed from the quantized DCT coefficient indices. Using methods developed in kernel theory a classifier is trained in a high dimensional feature space which is capable of discriminating original from stegoimages. The algorithm is tested on the F5 hiding method.

Kernel Fisher discriminant for steganalysis of JPEG hiding methods

Constraining the reproduction alphabet to be of small size in encoding continuous-amplitude memoryless sources has been shown to give very small degradation from the ideal performance of the rate-distortion bound. The optimum fixed-size reproduction alphabet and its individual letter probabilities are required in order to encode the source with performance approaching that of theory. These can be found through a somewhat lengthy, but convergent, algorithm. Given reasonably chosen fixed sets of reproduction letters and/or their probabilities, we define new rate-distortion functions which are coding bounds under these alphabet constraints. We calculate these functions for the Gaussian and Laplacian sources and the squared-error distortion measure and find that performance near the rate-distortion bound is achievable using a reproduction alphabet consisting of a small number of optimum quantizer levels.

Source coding bounds using quantizer reproduction levels (Corresp.)

This paper first introduces an asymmetric tree structure for utilization with an error resilient form 3-D SPIHT, called ERC-SPIHT. Then, we present a fast error concealment scheme, borrowed from Rane et al.'s work with images, for embedded video bitstream using ERC-SPIHT. In addition to using simple averaging method in the root subband, we detect the presence or absence of edges in the lost block of every image. Then we use an interpolation scheme to recover the lost edge information.

https://www.ecse.rpi.edu/~pearlman/papers/ei03_cp.pdf

Error-resilient video coding with improved 3D SPIHT and error concealment

Progressive Video Coding for Noisy Channels

A very fast, low complexity algorithm for resolution scalable and random access decoding is presented. The algorithm avoids the multiple passes of bit-plane coding for speed improvement. The decrease in dynamic ranges of wavelet coefficients magnitudes is efficiently coded. The hierarchical dynamic range coding naturally enables a resolution scalable representation of a wavelet transformed image.

William A. Pearlman

Papers

Kernel Fisher discriminant for steganalysis of JPEG hiding methods

Source coding bounds using quantizer reproduction levels (Corresp.)

Error-resilient video coding with improved 3D SPIHT and error concealment

Progressive Video Coding for Noisy Channels

Low complexity resolution progressive image coding algorithm: progres (progressive resolution decompression)